Aim We seek to demonstrate that whilst information derived from phylogeographic and landscape genetic approaches has been used broadly to further ecological and evolutionary hypothesis testing, it can also be used to further species modelling approaches, particularly where bioclimatic and demographic methodologies are to be combined to tackle climate change adaptation and conservation planning.
Location General application.
Methods We start with a review of species distribution modelling studies that have used data derived from molecular marker studies, and identify which parameters can realistically be derived from molecular marker studies for inclusion in species and ecosystem distribution prediction and conservation planning.
Results We find that the uptake of phylogeographic and landscape genetic methods to inform species distribution modelling studies has to date been limited (particularly the latter approaches), despite offering clear potential to improve species modelling approaches that aim to combine climatic envelope and demographic parameters. Using a series of cases studies, we demonstrate that phylogeographic approaches can be particularly useful for identifying biogeographic barriers and refugia, testing alternative demographic models, identifying concordant demographic patterns between species within a single ecosystem and testing temporal niche conservatism. We also find that landscape genetic approaches are particularly useful for quantifying landscape permeability and source/sink dynamics of meta-populations and identifying adaptive variation in the landscape. A summary of parameters that are derivable from such studies for modelling and conservation applications is provided.
Main conclusions Molecular marker methods have much to offer species distribution modelling, particularly in the field of climate adaptation. Molecular information can inform on species historical dynamics and contemporary demography necessary to advance species modelling paradigms that seek to integrate climatic and demographic drivers. Furthermore, recognizing diversity below species level and incorporating this information into modelling frameworks will enable conservation managers to plan for the capture of areas of evolutionary potential.